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GitHub Codespaces VS Keras

Compare GitHub Codespaces VS Keras and see what are their differences

GitHub Codespaces logo GitHub Codespaces

GItHub Codespaces is a hosted remote coding environment by GitHub based on Visual Studio Codespaces integrated directly for GitHub.

Keras logo Keras

Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
  • GitHub Codespaces Landing page
    Landing page //
    2023-09-01
  • Keras Landing page
    Landing page //
    2023-10-16

GitHub Codespaces videos

Brief introduction of GitHub Codespaces

More videos:

  • Review - GitHub Codespaces First Look - 5 things to look for

Keras videos

3. Deep Learning Tutorial (Tensorflow2.0, Keras & Python) - Movie Review Classification

More videos:

  • Review - Movie Review Classifier in Keras | Deep Learning | Binary Classifier
  • Review - EKOR KERAS!! Review and Bike Check DARTMOOR HORNET 2018 // MTB Indonesia

Category Popularity

0-100% (relative to GitHub Codespaces and Keras)
Text Editors
100 100%
0% 0
Data Science And Machine Learning
IDE
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare GitHub Codespaces and Keras

GitHub Codespaces Reviews

12 Best Online IDE and Code Editors to Develop Web Applications
Beginners who want to try their luck can use GitHub Codespaces for free with limited benefits, but you will have enough features to carry on. If you are a team or an enterprise, you can start using GitHub Codespaces at $40/user/year.
Source: geekflare.com

Keras Reviews

10 Python Libraries for Computer Vision
TensorFlow and Keras are widely used libraries for machine learning, but they also offer excellent support for computer vision tasks. TensorFlow provides pre-trained models like Inception and ResNet for image classification, while Keras simplifies the process of building, training, and evaluating deep learning models.
Source: clouddevs.com
25 Python Frameworks to Master
Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by François Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.
Source: kinsta.com
15 data science tools to consider using in 2021
Keras is a programming interface that enables data scientists to more easily access and use the TensorFlow machine learning platform. It's an open source deep learning API and framework written in Python that runs on top of TensorFlow and is now integrated into that platform. Keras previously supported multiple back ends but was tied exclusively to TensorFlow starting with...

Social recommendations and mentions

Based on our record, GitHub Codespaces should be more popular than Keras. It has been mentiond 143 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

GitHub Codespaces mentions (143)

  • From Text Editors to Cloud-based IDEs - a DevEx journey
    Then, we had the rise of the cloud and the arrival of cloud-based IDEs. The first cloud-based IDE was PHPanywhere (eventually becoming CodeAnywhere) in 2009, followed by Cloud9 in 2010 (before AWS bought it in 2016), Glitch (2018), GitPod (2019), GitHub Codespaces (2020), and Google’s Project IDX (2024). - Source: dev.to / 3 days ago
  • Mastering Code Quality: Setting Up ESLint with Standard JS in TypeScript Projects
    If your team is using a Cloud Development Environment such as GitHub Codespaces, or Dev Containers such as Docker, you can even share the installation of dbaeumer.vscode-eslint with your teammates, via devcontainer.json. - Source: dev.to / about 1 month ago
  • Coding on tab s9 ultra
    Https://github.com/features/codespaces Currently, it is probably the most convenient for coding on mobile devices. Source: 6 months ago
  • Learning Angular
    I am currently right now viewing Angular Essential Training (paid by my company but I have a personal Pluralsight) and using GitHub Codespaces for $4 a month to host the virtuals created for such coding/learning. Source: 6 months ago
  • Amazon CodeCatalyst - Is it ready for the enterprise?
    I’m very interested in recent advancements in cloud-hosted development environments. GitHub Codespaces is the option I have the most experience with and the one I use more generally. With cloud-hosted development environments, your local machine becomes more of a thin client that facilitates access to the internet and the development environment. That is a considerable step toward enabling better education in... - Source: dev.to / 6 months ago
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Keras mentions (32)

  • Using Google Magika to build an AI-powered file type detector
    The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / 3 days ago
  • My Favorite DevTools to Build AI/ML Applications!
    As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / about 2 months ago
  • Getting Started with Gemma Models
    After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow. - Source: dev.to / about 2 months ago
  • How popular are libraries in each technology
    Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks. - Source: dev.to / 12 months ago
  • Official Question Thread! Ask /r/photography anything you want to know about photography or cameras! Don't be shy! Newbies welcome!
    I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them. Source: about 1 year ago
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What are some alternatives?

When comparing GitHub Codespaces and Keras, you can also consider the following products

replit - Code, create, andlearn together. Use our free, collaborative, in-browser IDE to code in 50+ languages — without spending a second on setup.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

CloudShell - Cloud Shell is a free admin machine with browser-based command-line access for managing your infrastructure and applications on Google Cloud Platform.

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

StackBlitz - Online VS Code Editor for Angular and React

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.